Big Data: What You Should Know. Mark Child Research Manager - Software IDC CEMA

Transcription

1 Big Data: What You Should Know Mark Child Research Manager - Software IDC CEMA

2 Agenda Market Dynamics Defining Big Data Technology Trends Information and Intelligence Market Realities Future Applications IDC Visit us at IDC.com and follow us on 2

3 The IT Market and the 3 rd Platform The third platform is driven by four forces: mobile broadband, devices and applications; social business; cloud services; and Big Data and analytics. This platform revolves around: Millions of applications Billions of users Trillions of connected fixed and mobile devices The second platform was that of client-server or where PCs and servers were connected through LANs and the internet, accompanied by tens of thousands of applications and hundreds of millions of users. The first platform was an industry characterized by mainframe computers and terminals with thousands of applications being delivered to millions of users. 3

4 Data Growing Unabated Information will grow by factor of 44 from 2009 to ZB* 35 ZB* Storage capacity will grow by a factor of 30 IT staffing will grow by a factor of 1.4 *Zettabyte = 1 trillion gigabytes 4

5 Sources of Data Growth Office Apps Enterprise Apps Web Apps Data creation is part of our daily lives Digital security Connected devices and media Social networks Software as a Service 5

6 Acceleration in the Adoption of Storage-Efficient Technologies Growth Factor 44x Storage Efficiency Data Growth Storage Efficiency Technologies Gap Storage Growth 30x Storage Virtualization - CAPEX, Migration costs, Management overhead, Scalability, Uptime Caching/SSD - SLA/QoS, Floorspace, Power Thin Provisioning - Reclaim unused capacity Tiering - Raw cost / per capacity Deduplication, Compression - Get rid of copies, Data footprint Unified/Converged Mgmt. - Management overhead Hypervisor integration - VM provisioning overhead Integrated snapshots and replication - DP & DR overhead FCoE, iscsi - Storage network costs 6

7 Acceleration in the Adoption of Information- Efficient Technologies Growth Factor Information Efficiency Information Efficiency Gap 67x Advanced Analytics Software (Embedded and Stand-alone) EQRA End-user Query, Reporting and Analysis Data Warehouse Generation and Management Content Analysis Tools Hadoop, Hbase, Map reduce Data Objects Growth Staffing Growth 7

8 What is Big Data? Value Volume Velocity Variety IDC defines Big Data technologies as a new generation of technologies and architectures, designed to economically extract value from very large volumes of a wide variety of data, by enabling high velocity capture, discovery and/or analysis. 8

9 How does Big Data differ from Business Analytics? Greater volumes of data than ever before Volumes growing quickly Cost reduction preventing system and manufacturing faults Revenue generation preventing online store outages Value Volume Velocity Variety Data processing in near-real-time (e.g. processing system logs to predict and prevent faults) Sensor data Not just RDBMS data but unstructured information e.g. System logs Social information 9

10 Data Source Big Data Output Processmediated data Transactional Tabular Relational Metadata Operational Structured Managed Regulated System Machinegenerated data Sensor data Computer logs Structured Reliable Fast High volume The Internet of Things Human-sourced information Social Multimedia Loosely structured or unstructured Unregulated Subjective Insightful Unreliable? Requires standardization IDC Visit us at IDC.com and follow us on 10

11 Is This Big Data? Collaboration Enterprise collaboration Collaborative BI Social Platforms BI and Analytics Statistics Data Mining Operations Research Hive and Pig Data Access SQL In-database Analytics MapReduce Storage Data Warehouse Other RDB Analytic sandbox HDFS Integration Extract, Transform and Load Data Quality, Profiling, Cleansing Master Data Management Data Attachment Data Sources CRM ERP POS Other RDB RFID/ Sensors Web/ Machine logs Social data 11

12 IDC's Big Data Technology and Services Market Sizing Criteria IDC Visit us at IDC.com and follow us on 12

13 Worldwide Big Data Technology and Services 3,1% 11,8% Revenue Share 41,5% by Segment, ,0% 29,7% Services Software Servers Storage Networking Total: $4.8 billion Source: IDC, 2012 IDC Visit us at IDC.com and follow us on 13

14 The Big Data technology stack Source: IDC, 2012 IDC Visit us at IDC.com and follow us on 14

15 Big Data and Analytics: The Chief CIO Issue from 2013 Onwards CIOs are being overwhelmed by the amount of data they are asked to manage Big Data Software Landscape Big Data and Analytics will be the issue of the year for many CIOs in 2013 in an effort to provide more value from IT CIOs will conduct numerous pilot analytics projects not all will succeed until they find the right tools and data models to provide best value Source: IDC,

16 Big Data technology and services use cases IDC Visit us at IDC.com and follow us on 16

17 The Value Of Information Where To Find It Increased revenue Improved business agility Cash flow increase Information Increased customer satisfaction or loyalty Increased employee productivity Operating cost reductions 17

18 Data Usage Being Practical Out of 100% of data saved, only 15% is accessed in future. Out of 15% 65% is accessed only once. 18

19 How much data does your organization currently process per day? 21,7% 2,3% 39,7% 11,3% 8,3% 1,5% 15,2% 0 TB Up to 1 TB 1TB to less than 5TBs 10TBs to less than 20TBs Don't know 5TBs to less than 10TBs 20TBs or more Source: IDC IT Buyers Pulse 2012 N=566 companies across CZ, HU, PL, RO, RU IDC Visit us at IDC.com and follow us on 19

20 What are the key areas that benefit (or would benefit) the most from leveraging Big Data solutions in your organization? Optimizing internal operations Better customer analytics Managing financial data Analyzing profitability Better predictive analytics Generating new revenue Managing risk levels Optimizing revenue Source: IDC IT Buyers Pulse 2012 Marketing campaign optimization Enabling innovative business models Potential for new insights that create competitive advantage N=425 companies across CZ, HU, PL, RO, RU 0% 10% 20% 30% 40% IDC Visit us at IDC.com and follow us on 20

21 Big Data and Intelligent Security Reactive Proactive Predictive Monitoring and logging, SIEM help enable shift from reactive to proactive security measures Big Data s ability to process large volumes of raw data in real time can enable shift from proactive to predictive security: Pattern recognition and predictive analytics Link to automated defensive systems: network traffic blocking, system quarantine, extended identity verification Risk analysis and risk management Integration with GRC systems IDC Visit us at IDC.com and follow us on 21

22 Big future for big data? IDC Visit us at IDC.com and follow us on 22

23 Challenges Personnel and skills Data governance Sponsorship Data classification, lifecycle and flow Implementing business process changes IDC Visit us at IDC.com and follow us on 23

24 Thank you! Mark Child Research Manager - Software IDC CEMA mchild@idc.com IDC Visit us at IDC.com and follow us on 24